Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE (Open Access)

Comparing two methods to measure oxidative pyrolysis gases in a wind tunnel and in prescribed burns

David R. Weise https://orcid.org/0000-0002-9671-7203 A * , Timothy J. Johnson https://orcid.org/0000-0001-9514-6288 B , Tanya L. Myers https://orcid.org/0000-0001-8995-7033 B , Wei Min Hao https://orcid.org/0000-0002-5604-8762 C , Stephen Baker C , Javier Palarea-Albaladejo https://orcid.org/0000-0003-0162-669X D , Nicole K. Scharko B , Ashley M. Bradley https://orcid.org/0000-0001-7344-9640 B , Catherine A. Banach https://orcid.org/0000-0001-6038-1624 B and Russell G. Tonkyn https://orcid.org/0000-0002-3955-3556 B
+ Author Affiliations
- Author Affiliations

A USDA Forest Service, Pacific Southwest Research Station, Riverside, CA 92507, USA.

B Pacific Northwest National Laboratory, Richland, WA 99352, USA.

C USDA Forest Service, Rocky Mountain Research Station, Missoula, MT 59808, USA.

D Department of Computer Sciences, Applied Mathematics and Statistics, University of Girona, Girona, Spain.

* Correspondence to: david.weise@usda.gov

International Journal of Wildland Fire 32(1) 56-77 https://doi.org/10.1071/WF22079
Submitted: 24 May 2022  Accepted: 28 October 2022   Published: 30 November 2022

© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution 4.0 International License (CC BY).

Abstract

Background: Fire models use pyrolysis data from ground samples and environments that differ from wildland conditions. Two analytical methods successfully measured oxidative pyrolysis gases in wind tunnel and field fires: Fourier transform infrared (FTIR) spectroscopy and gas chromatography with flame-ionisation detector (GC-FID). Compositional data require appropriate statistical analysis.

Aims: To determine if oxidative pyrolysis gas composition differed between analytical methods and locations (wind tunnel and field).

Methods: Oxidative pyrolysis gas sample composition collected in wind tunnel and prescribed fires was determined by FTIR and GC/FID. Proportionality between gases was tested. Analytical method and location effects on composition were tested using permutational multivariate analysis of variance and the Kruskal–Wallis test.

Key results: Gases proportional to each other were identified. The FTIR composition differed between locations. The subcomposition of common gases differed between analytical methods but not between locations. Relative amount of the primary fuel gases (CO, CH4) was not significantly affected by location.

Conclusions: Composition of trace gases differed between the analytical methods; however, each method yielded a comparable description of the primary fuel gases.

Implications: Both FTIR and GC/FID methods can be used to quantify primary pyrolysis fuel gases for physically-based fire models. Importance of the trace gases in combustion models remains to be determined.

Keywords: compositional data analysis, Fourier transform infrared spectroscopy, FTIR, gas chromatography/flame ionisation detector, gas composition, GC/FID, log-ratio, Pinus palustris.


References

Aitchison J (1982) The statistical analysis of compositional data. Journal of the Royal Statistical Society: Series B (Methodological) 44, 139–160.
The statistical analysis of compositional data.Crossref | GoogleScholarGoogle Scholar |

Aitchison J (1986) ‘The statistical analysis of compositional data.’ (Chapman and Hall: London, New York)

Aitchison J, Barceló-Vidal C, Martín-Fernández JA, Pawlowsky-Glahn V (2000) Logratio analysis and compositional distance. Mathematical Geology 32, 271–275.
Logratio analysis and compositional distance.Crossref | GoogleScholarGoogle Scholar |

Akagi SK, Yokelson RJ, Wiedinmyer C, Alvarado MJ, Reid JS, Karl T, Crounse JD, Wennberg PO (2011) Emission factors for open and domestic biomass burning for use in atmospheric models. Atmospheric Chemistry and Physics 11, 4039–4072.
Emission factors for open and domestic biomass burning for use in atmospheric models.Crossref | GoogleScholarGoogle Scholar |

Akagi SK, Burling IR, Mendoza A, Johnson TJ, Cameron M, Griffith DWT, Paton-Walsh C, Weise DR, Reardon J, Yokelson RJ (2014) Field measurements of trace gases emitted by prescribed fires in southeastern US pine forests using an open-path FTIR system. Atmospheric Chemistry and Physics 14, 199–215.
Field measurements of trace gases emitted by prescribed fires in southeastern US pine forests using an open-path FTIR system.Crossref | GoogleScholarGoogle Scholar |

Alessio GA, Peñuelas J, Llusià J, Ogaya R, Estiarte M, De Lillis M (2008) Influence of water and terpenes on flammability in some dominant Mediterranean species. International Journal of Wildland Fire 17, 274
Influence of water and terpenes on flammability in some dominant Mediterranean species.Crossref | GoogleScholarGoogle Scholar |

Amini E, Safdari M-S, DeYoung JT, Weise DR, Fletcher TH (2019a) Characterization of pyrolysis products from slow pyrolysis of live and dead vegetation native to the southern United States. Fuel 235, 1475–1491.
Characterization of pyrolysis products from slow pyrolysis of live and dead vegetation native to the southern United States.Crossref | GoogleScholarGoogle Scholar |

Amini E, Safdari M-S, Weise DR, Fletcher TH (2019b) Pyrolysis kinetics of live and dead wildland vegetation from the southern United States. Journal of Analytical and Applied Pyrolysis 142, 104613
Pyrolysis kinetics of live and dead wildland vegetation from the southern United States.Crossref | GoogleScholarGoogle Scholar |

Anderson MJ (2001) A new method for non-parametric multivariate analysis of variance. Austral Ecology 26, 32–46.
A new method for non-parametric multivariate analysis of variance.Crossref | GoogleScholarGoogle Scholar |

Anderson MJ (2017) Permutational Multivariate Analysis of Variance (PERMANOVA). In ‘Wiley StatsRef: Statistics Reference Online’. (Eds N Balakrishnan, T Colton, B Everitt, W Piegorsch, F Ruggeri, JL Teugels) pp. 1–15. (John Wiley & Sons, Ltd: Chichester, UK)
| Crossref |

Anderson HE, Rothermel RC (1965) Influence of moisture and wind upon the characteristics of free-burning fires. Symposium (International) on Combustion 10, 1009–1019.
Influence of moisture and wind upon the characteristics of free-burning fires.Crossref | GoogleScholarGoogle Scholar |

Andreae MO, Merlet P (2001) Emission of trace gases and aerosols from biomass burning. Global Biogeochemical Cycles 15, 955–966.
Emission of trace gases and aerosols from biomass burning.Crossref | GoogleScholarGoogle Scholar |

Austin CC, Wang D, Ecobichon DJ, Dussault G (2001) Characterization of volatile organic compounds in smoke at experimental fires. Journal of Toxicology and Environmental Health, Part A 63, 191–206.
Characterization of volatile organic compounds in smoke at experimental fires.Crossref | GoogleScholarGoogle Scholar |

Banach CA, Bradley AM, Tonkyn RG, Williams ON, Chong J, Weise DR, Myers TL, Johnson TJ (2021) Dynamic infrared gas analysis from longleaf pine fuel beds burned in a wind tunnel: observation of phenol in pyrolysis and combustion phases. Atmospheric Measurement Techniques 14, 2359–2376.
Dynamic infrared gas analysis from longleaf pine fuel beds burned in a wind tunnel: observation of phenol in pyrolysis and combustion phases.Crossref | GoogleScholarGoogle Scholar |

Bandeen-Roche K (1994) Resolution of additive mixtures into source components and contributions: a compositional approach. Journal of the American Statistical Association 89, 1450–1458.
Resolution of additive mixtures into source components and contributions: a compositional approach.Crossref | GoogleScholarGoogle Scholar |

Barnard B, Young D (2018) covTestR: Covariance Matrix Tests. Available at https://CRAN.R-project.org/package=covTestR

Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological) 57, 289–300.
Controlling the false discovery rate: a practical and powerful approach to multiple testing.Crossref | GoogleScholarGoogle Scholar |

Borujerdi PR, Shotorban B, Mahalingam S, Weise DR (2022) Influence of pyrolysis gas composition and reaction kinetics on leaf-scale fires. Combustion Science and Technology
Influence of pyrolysis gas composition and reaction kinetics on leaf-scale fires.Crossref | GoogleScholarGoogle Scholar |

Boubel RW, Darley EF, Schuck EA (1969) Emissions from burning grass stubble and straw. Journal of the Air Pollution Control Association 19, 497–500.
Emissions from burning grass stubble and straw.Crossref | GoogleScholarGoogle Scholar |

Brauer CS, Blake TA, Guenther AB, Sharpe SW, Sams RL, Johnson TJ (2014) Quantitative infrared absorption cross sections of isoprene for atmospheric measurements. Atmospheric Measurement Techniques 7, 3839–3847.
Quantitative infrared absorption cross sections of isoprene for atmospheric measurements.Crossref | GoogleScholarGoogle Scholar |

Bruker Corporation LLC (2020) OPUS software, v. 5.5. (Billerica, MA, USA)

Burling IR, Yokelson RJ, Griffith DWT, Johnson TJ, Veres P, Roberts JM, Warneke C, Urbanski SP, Reardon J, Weise DR, Hao WM, de Gouw J (2010) Laboratory measurements of trace gas emissions from biomass burning of fuel types from the southeastern and southwestern United States. Atmospheric Chemistry and Physics 10, 11115–11130.
Laboratory measurements of trace gas emissions from biomass burning of fuel types from the southeastern and southwestern United States.Crossref | GoogleScholarGoogle Scholar |

Butler BM, Palarea-Albaladejo J, Shepherd KD, Nyambura KM, Towett EK, Sila AM, Hillier S (2020) Mineral–nutrient relationships in African soils assessed using cluster analysis of X-ray powder diffraction patterns and compositional methods. Geoderma 375, 114474
Mineral–nutrient relationships in African soils assessed using cluster analysis of X-ray powder diffraction patterns and compositional methods.Crossref | GoogleScholarGoogle Scholar |

Chetehouna K, Barboni T, Zarguili I, Leoni E, Simeoni A, Fernandez-Pello AC (2009) Investigation on the emission of volatile organic compounds from heated vegetation and their potential to cause an accelerating forest fire. Combustion Science and Technology 181, 1273–1288.
Investigation on the emission of volatile organic compounds from heated vegetation and their potential to cause an accelerating forest fire.Crossref | GoogleScholarGoogle Scholar |

Christian TJ, Kleiss B, Yokelson RJ, Holzinger R, Crutzen PJ, Hao WM, Shirai T, Blake DR (2004) Comprehensive laboratory measurements of biomass-burning emissions: 2. First intercomparison of open-path FTIR, PTR-MS, and GC-MS/FID/ECD. Journal of Geophysical Research 109, D02311
Comprehensive laboratory measurements of biomass-burning emissions: 2. First intercomparison of open-path FTIR, PTR-MS, and GC-MS/FID/ECD.Crossref | GoogleScholarGoogle Scholar |

Collard F-X, Blin J (2014) A review on pyrolysis of biomass constituents: mechanisms and composition of the products obtained from the conversion of cellulose, hemicelluloses and lignin. Renewable and Sustainable Energy Reviews 38, 594–608.
A review on pyrolysis of biomass constituents: mechanisms and composition of the products obtained from the conversion of cellulose, hemicelluloses and lignin.Crossref | GoogleScholarGoogle Scholar |

Conover WJ (1999) ‘Practical nonparametric statistics.’ (Wiley: New York)

Crutzen PJ, Brauch HG (Eds) (2016) ‘Paul J. Crutzen: a pioneer on atmospheric chemistry and climate in the anthropocene.’ (Springer: Zürich)

Crutzen PJ, Heidt LE, Krasnec JP, Pollock WH, Seiler W (1979) Biomass burning as a source of atmospheric gases CO, H2, N20, NO, CH3Cl and COS. Nature 282, 253–256.
Biomass burning as a source of atmospheric gases CO, H2, N20, NO, CH3Cl and COS.Crossref | GoogleScholarGoogle Scholar |

Darley EF, Burleson FR, Mateer EH, Middleton JT, Osterli VP (1966) Contribution of Burning of Agricultural Wastes to Photochemical Air Pollution. Journal of the Air Pollution Control Association 16, 685–690.
Contribution of Burning of Agricultural Wastes to Photochemical Air Pollution.Crossref | GoogleScholarGoogle Scholar |

Di Blasi C (2008) Modeling chemical and physical processes of wood and biomass pyrolysis. Progress in Energy and Combustion Science 34, 47–90.
Modeling chemical and physical processes of wood and biomass pyrolysis.Crossref | GoogleScholarGoogle Scholar |

Dimitrakopoulos AP (2001) Thermogravimetric analysis of Mediterranean plant species. Journal of Analytical and Applied Pyrolysis 60, 123–130.
Thermogravimetric analysis of Mediterranean plant species.Crossref | GoogleScholarGoogle Scholar |

Egozcue JJ, Pawlowsky-Glahn V (2005) Groups of parts and their balances in compositional data analysis. Mathematical Geology 37, 795–828.
Groups of parts and their balances in compositional data analysis.Crossref | GoogleScholarGoogle Scholar |

Egozcue JJ, Pawlowsky-Glahn V, Gloor GB (2018) Linear association in compositional data analysis. Austrian Journal of Statistics 47, 3
Linear association in compositional data analysis.Crossref | GoogleScholarGoogle Scholar |

Engle M, Martín-Fernández JA, Geboy N, Olea RA, Peucker-Ehrenbrink B, Kolker A, Krabbenhoft D, Lamothe P, Bothner M, Tate M (2011) Source apportionment of atmospheric trace gases and particulate matter: comparison of log-ratio and traditional approaches. In ‘Proceedings of the 4th International Workshop on Compositional Data Analysis’, Girona, Spain. p. 10. (Universitat de Girona: Girona, Spain) Available at http://hdl.handle.net/10256/13626

EPA (1999) Compendium Method TO-14A Determination Of Volatile Organic Compounds (VOCs) In Ambient Air Using Specially Prepared Canisters With Subsequent Analysis By Gas Chromatography. In ‘Compendium of Methods for the Determination of Toxic Organic Compounds in Ambient Air’. 86pp. (Environmental Protection Agency: Cincinnati, OH) Available at https://www.epa.gov/sites/production/files/2019-11/documents/to-14ar.pdf

Erb I, Notredame C (2016) How should we measure proportionality on relative gene expression data. Theory in Biosciences 135, 21–36.
How should we measure proportionality on relative gene expression data.Crossref | GoogleScholarGoogle Scholar |

Evans JC, Huckaby JL, Mitroshkov AV, Julya JL, Hayes JC, Edwards JA, Sasaki LM (1998) 32-week holding-time study of SUMMA polished canisters and triple sorbent traps used to sample organic constituents in radioactive waste tank vapor headspace. Environmental Science & Technology 32, 3410–3417.
32-week holding-time study of SUMMA polished canisters and triple sorbent traps used to sample organic constituents in radioactive waste tank vapor headspace.Crossref | GoogleScholarGoogle Scholar |

Fehsenfeld FC, Dickerson RR, Hübler G, Luke WT, Nunnermacker LJ, Williams EJ, Roberts JM, Calvert JG, Curran CM, Delany AC, Eubank CS, Fahey DW, Fried A, Gandrud BW, Langford AO, Murphy PC, Norton RB, Pickering KE, Ridley BA (1987) A ground-based intercomparison of NO, NOx, and NOy measurement techniques. Journal of Geophysical Research 92, 14710
A ground-based intercomparison of NO, NOx, and NOy measurement techniques.Crossref | GoogleScholarGoogle Scholar |

Fleming PJ, Wallace JJ (1986) How not to lie with statistics: the correct way to summarize benchmark results. Commun ACM 29, 218–221.
How not to lie with statistics: the correct way to summarize benchmark results.Crossref | GoogleScholarGoogle Scholar |

Gibergans-Baguena J, Hervada-Sala C, Jarauta-Bragulat E (2020) The quality of urban air in Barcelona: a new approach applying compositional data analysis methods. Emerging Science Journal 4, 113–121.
The quality of urban air in Barcelona: a new approach applying compositional data analysis methods.Crossref | GoogleScholarGoogle Scholar |

Gordon IE, Rothman LS, Hill C, Kochanov RV, Tan Y, Bernath PF, Birk M, Boudon V, Campargue A, Chance KV, Drouin BJ, Flaud J-M, Gamache RR, Hodges JT, Jacquemart D, Perevalov VI, Perrin A, Shine KP, Smith M-AH, Tennyson J, Toon GC, Tran H, Tyuterev VG, Barbe A, Császár AG, Devi VM, Furtenbacher T, Harrison JJ, Hartmann J-M, Jolly A, Johnson TJ, Karman T, Kleiner I, Kyuberis AA, Loos J, Lyulin OM, Massie ST, Mikhailenko SN, Moazzen-Ahmadi N, Müller HSP, Naumenko OV, Nikitin AV, Polyansky OL, Rey M, Rotger M, Sharpe SW, Sung K, Starikova E, Tashkun SA, Auwera JV, Wagner G, Wilzewski J, Wcisło P, Yu S, Zak EJ (2017) The HITRAN2016 molecular spectroscopic database. Journal of Quantitative Spectroscopy and Radiative Transfer 203, 3–69.
The HITRAN2016 molecular spectroscopic database.Crossref | GoogleScholarGoogle Scholar |

Griffith DWT (1996) Synthetic calibration and quantitative analysis of gas-phase FT-IR spectra. Applied Spectroscopy 50, 59–70.
Synthetic calibration and quantitative analysis of gas-phase FT-IR spectra.Crossref | GoogleScholarGoogle Scholar |

Griffith DWT, Deutscher NM, Caldow C, Kettlewell G, Riggenbach M, Hammer S (2012) A Fourier transform infrared trace gas and isotope analyser for atmospheric applications. Atmospheric Measurement Techniques 5, 2481–2498.
A Fourier transform infrared trace gas and isotope analyser for atmospheric applications.Crossref | GoogleScholarGoogle Scholar |

Haase KB, Keene WC, Pszenny AAP, Mayne HR, Talbot RW, Sive BC (2012) Calibration and intercomparison of acetic acid measurements using proton-transfer-reaction mass spectrometry (PTR-MS. Atmospheric Measurement Techniques 5, 2739–2750.
Calibration and intercomparison of acetic acid measurements using proton-transfer-reaction mass spectrometry (PTR-MS.Crossref | GoogleScholarGoogle Scholar |

Herzog MM, Hudak AT, Weise DR, Bradley AM, Tonkyn RG, Banach CA, Myers TL, Bright BC, Batchelor JL, Kato A, Maitland JS, Johnson TJ (2022) Point cloud based mapping of understory shrub fuel distribution, estimation of fuel consumption and relationship to pyrolysis gas emissions on experimental prescribed burns Fire 5, 118
Point cloud based mapping of understory shrub fuel distribution, estimation of fuel consumption and relationship to pyrolysis gas emissions on experimental prescribed burnsCrossref | GoogleScholarGoogle Scholar |

Hollander M, Wolfe DA, Chicken E (2014) ‘Nonparametric statistical methods.’ (John Wiley & Sons, Inc: Hoboken, NJ)

Hudak AT, Kato A, Bright BC, Loudermilk EL, Hawley C, Restaino JC, Ottmar RD, Prata GA, Cabo C, Prichard SJ, Rowell EM, Weise DR (2020) Towards spatially explicit quantification of pre- and postfire fuels and fuel consumption from traditional and point cloud measurements. Forest Science 66, 428–442.
Towards spatially explicit quantification of pre- and postfire fuels and fuel consumption from traditional and point cloud measurements.Crossref | GoogleScholarGoogle Scholar |

Jarauta-Bragulat E, Hervada-Sala C, Egozcue JJ (2016) Air Quality Index revisited from a compositional point of view. Mathematical Geosciences 48, 581–593.
Air Quality Index revisited from a compositional point of view.Crossref | GoogleScholarGoogle Scholar |

Johnson TJ, Masiello T, Sharpe SW (2006) The quantitative infrared and NIR spectrum of CH2I2 vapor: vibrational assignments and potential for atmospheric monitoring. Atmospheric Chemistry and Physics 6, 2581–2591.
The quantitative infrared and NIR spectrum of CH2I2 vapor: vibrational assignments and potential for atmospheric monitoring.Crossref | GoogleScholarGoogle Scholar |

Johnson TJ, Profeta LTM, Sams RL, Griffith DWT, Yokelson RL (2010) An infrared spectral database for detection of gases emitted by biomass burning. Vibrational Spectroscopy 53, 97–102.
An infrared spectral database for detection of gases emitted by biomass burning.Crossref | GoogleScholarGoogle Scholar |

Kajos MK, Rantala P, Hill M, Hellén H, Aalto J, Patokoski J, Taipale R, Hoerger CC, Reimann S, Ruuskanen TM, Rinne J, Petäjä T (2015) Ambient measurements of aromatic and oxidized VOCs by PTR-MS and GC-MS: intercomparison between four instruments in a boreal forest in Finland. Atmospheric Measurement Techniques 8, 4453–4473.
Ambient measurements of aromatic and oxidized VOCs by PTR-MS and GC-MS: intercomparison between four instruments in a boreal forest in Finland.Crossref | GoogleScholarGoogle Scholar |

Kochanov RV, Gordon IE, Rothman LS, Shine KP, Sharpe SW, Johnson TJ, Wallington TJ, Harrison JJ, Bernath PF, Birk M, Wagner G, Le Bris K, Bravo I, Hill C (2019) Infrared absorption cross-sections in HITRAN2016 and beyond: Expansion for climate, environment, and atmospheric applications. Journal of Quantitative Spectroscopy and Radiative Transfer 230, 172–221.
Infrared absorption cross-sections in HITRAN2016 and beyond: Expansion for climate, environment, and atmospheric applications.Crossref | GoogleScholarGoogle Scholar |

Korkmaz S, Goksuluk D, Zararsiz G (2014) MVN: An R Package for assessing multivariate normality. The R Journal 6, 151–162.
MVN: An R Package for assessing multivariate normality.Crossref | GoogleScholarGoogle Scholar |

Li H, Lamb KD, Schwarz JP, Selimovic V, Yokelson RJ, McMeeking GR, May AA (2019) Inter-comparison of black carbon measurement methods for simulated open biomass burning emissions. Atmospheric Environment 206, 156–169.
Inter-comparison of black carbon measurement methods for simulated open biomass burning emissions.Crossref | GoogleScholarGoogle Scholar |

Lobert JM, Scharffe DH, Hao WM, Crutzen PJ (1990) Importance of biomass burning in the atmospheric budgets of nitrogen-containing gases. Nature 346, 552–554.
Importance of biomass burning in the atmospheric budgets of nitrogen-containing gases.Crossref | GoogleScholarGoogle Scholar |

Lovell D, Pawlowsky-Glahn V, Egozcue JJ, Marguerat S, Bähler J (2015) Proportionality: a valid alternative to correlation for relative data. PLoS Computational Biology 11, e1004075
Proportionality: a valid alternative to correlation for relative data.Crossref | GoogleScholarGoogle Scholar |

Ludovici K, Eaton R, Zarnoch S (2018) Longleaf pine site response to repeated fertilization and forest floor removal by raking and prescribed burning. e-Research Paper RP-SRS-60. (USDA Forest Service Southern Research Station: Asheville, NC) Available at https://www.fs.usda.gov/treesearch/pubs/55619

Matt FJ, Dietenberger MA, Weise DR (2020) Summative and ultimate analysis of live leaves from southern U.S. forest plants for use in fire modeling. Energy & Fuels 34, 4703–4720.
Summative and ultimate analysis of live leaves from southern U.S. forest plants for use in fire modeling.Crossref | GoogleScholarGoogle Scholar |

May AA, McMeeking GR, Lee T, Taylor JW, Craven JS, Burling I, Sullivan AP, Akagi S, Collett JL, Flynn M, Coe H, Urbanski SP, Seinfeld JH, Yokelson RJ, Kreidenweis SM (2014) Aerosol emissions from prescribed fires in the United States: A synthesis of laboratory and aircraft measurements Journal of Geophysical Research: Atmospheres 119, 11,826–11,849.
Aerosol emissions from prescribed fires in the United States: A synthesis of laboratory and aircraft measurementsCrossref | GoogleScholarGoogle Scholar |

Neves D, Thunman H, Matos A, Tarelho L, Gómez-Barea A (2011) Characterization and prediction of biomass pyrolysis products. Progress in Energy and Combustion Science 37, 611–630.
Characterization and prediction of biomass pyrolysis products.Crossref | GoogleScholarGoogle Scholar |

Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Szoecs E, Wagner H (2020) vegan: Community Ecology Package. Available at https://CRAN.R-project.org/package=vegan

Palarea-Albaladejo J, Martín-Fernández JA (2013) Values below detection limit in compositional chemical data. Analytica Chimica Acta 764, 32–43.
Values below detection limit in compositional chemical data.Crossref | GoogleScholarGoogle Scholar |

Palarea-Albaladejo J, Martín-Fernández JA (2015) zCompositions — R package for multivariate imputation of left-censored data under a compositional approach. Chemometrics and Intelligent Laboratory Systems 143, 85–96.
zCompositions — R package for multivariate imputation of left-censored data under a compositional approach.Crossref | GoogleScholarGoogle Scholar |

Pearson K (1897) Mathematical contributions to the theory of evolution.—On a form of spurious correlation which may arise when indices are used in the measurement of organs. Proceedings of the Royal Society of London 60, 489–498.
Mathematical contributions to the theory of evolution.—On a form of spurious correlation which may arise when indices are used in the measurement of organs.Crossref | GoogleScholarGoogle Scholar |

Philpot CW (1969) Seasonal changes in heat content and ether extractive content of chamise. Research Paper INT-61. (USDA Forest Service, Intermountain Forest and Range Experiment Station: Ogden, UT) Available at https://ia601005.us.archive.org/16/items/seasonalchangesi61phil/seasonalchangesi61phil.pdf

Philpot CW (1971) The pyrolysis products and thermal characteristics of cottonwood and its components. Research Paper INT-107. (USDA Forest Service, Intermountain Forest and Range Experiment Station: Ogden, UT).

Pistone K, Redemann J, Doherty S, Zuidema P, Burton S, Cairns B, Cochrane S, Ferrare R, Flynn C, Freitag S, Howell SG, Kacenelenbogen M, LeBlanc S, Liu X, Schmidt KS, Sedlacek III AJ, Segal-Rozenhaimer M, Shinozuka Y, Stamnes S, van Diedenhoven B, Van Harten G, Xu F (2019) Intercomparison of biomass burning aerosol optical properties from in situ and remote-sensing instruments in ORACLES-2016. Atmospheric Chemistry and Physics 19, 9181–9208.
Intercomparison of biomass burning aerosol optical properties from in situ and remote-sensing instruments in ORACLES-2016.Crossref | GoogleScholarGoogle Scholar |

Quinn TP, Richardson MF, Lovell D, Crowley TM (2017) propr: An R-package for identifying proportionally abundant features using compositional data analysis. Scientific Reports 7, 16252
propr: An R-package for identifying proportionally abundant features using compositional data analysis.Crossref | GoogleScholarGoogle Scholar |

Quinn TP, Erb I, Richardson MF, Crowley TM (2018) Understanding sequencing data as compositions: an outlook and review (J Wren, Ed.). Bioinformatics 34, 2870–2878.
Understanding sequencing data as compositions: an outlook and review (J Wren, Ed.).Crossref | GoogleScholarGoogle Scholar |

Quinn TP, Erb I, Gloor G, Notredame C, Richardson MF, Crowley TM (2019) A field guide for the compositional analysis of any-omics data. GigaScience 8, giz107
A field guide for the compositional analysis of any-omics data.Crossref | GoogleScholarGoogle Scholar |

Richards LW (1940) Effect of certain chemical attributes of vegetation on forest inflammability. Journal of Agricultural Research 60, 833–838.

Rogers JM, Susott RA, Kelsey RG (1986) Chemical composition of forest fuels affecting their thermal behavior. Canadian Journal of Forest Research 16, 721–726.
Chemical composition of forest fuels affecting their thermal behavior.Crossref | GoogleScholarGoogle Scholar |

Rothermel RC, Anderson HE (1966) Fire spread characteristics determined in the laboratory. Research Paper INT-30. (USDA Forest Service, Intermountain Forest and Range Experiment Station: Ogden, UT) Available at http://www.fs.fed.us/rm/pubs_int/int_rp030.pdf

Royston JP (1982) An extension of Shapiro and Wilk’s W test for normality to large samples. Applied Statistics 31, 115–124.
An extension of Shapiro and Wilk’s W test for normality to large samples.Crossref | GoogleScholarGoogle Scholar |

Safdari M-S, Rahmati M, Amini E, Howarth JE, Berryhill JP, Dietenberger M, Weise DR, Fletcher TH (2018) Characterization of pyrolysis products from fast pyrolysis of live and dead vegetation native to the Southern United States. Fuel 229, 151–166.
Characterization of pyrolysis products from fast pyrolysis of live and dead vegetation native to the Southern United States.Crossref | GoogleScholarGoogle Scholar |

Safdari M-S, Amini E, Weise DR, Fletcher TH (2019) Heating rate and temperature effects on pyrolysis products from live wildland fuels. Fuel 242, 295–304.
Heating rate and temperature effects on pyrolysis products from live wildland fuels.Crossref | GoogleScholarGoogle Scholar |

Safdari M-S, Amini E, Weise DR, Fletcher TH (2020) Comparison of pyrolysis of live wildland fuels heated by radiation vs. convection. Fuel 268, 117342
Comparison of pyrolysis of live wildland fuels heated by radiation vs. convection.Crossref | GoogleScholarGoogle Scholar |

Scharko NK, Oeck AM, Myers TL, Tonkyn RG, Banach CA, Baker SP, Lincoln EN, Chong J, Corcoran BM, Burke GM, Ottmar RD, Restaino JC, Weise DR, Johnson TJ (2019a) Gas-phase pyrolysis products emitted by prescribed fires in pine forests with a shrub understory in the southeastern United States. Atmospheric Chemistry and Physics 19, 9681–9698.
Gas-phase pyrolysis products emitted by prescribed fires in pine forests with a shrub understory in the southeastern United States.Crossref | GoogleScholarGoogle Scholar |

Scharko NK, Oeck AM, Tonkyn RG, Baker SP, Lincoln EN, Chong J, Corcoran BM, Burke GM, Weise DR, Myers TL, Banach CA, Griffith DWT, Johnson TJ (2019b) Identification of gas-phase pyrolysis products in a prescribed fire: first detections using infrared spectroscopy for naphthalene, methyl nitrite, allene, acrolein and acetaldehyde. Atmospheric Measurement Techniques 12, 763–776.
Identification of gas-phase pyrolysis products in a prescribed fire: first detections using infrared spectroscopy for naphthalene, methyl nitrite, allene, acrolein and acetaldehyde.Crossref | GoogleScholarGoogle Scholar |

Schott JR (2007) A test for the equality of covariance matrices when the dimension is large relative to the sample sizes. Computational Statistics & Data Analysis 51, 6535–6542.
A test for the equality of covariance matrices when the dimension is large relative to the sample sizes.Crossref | GoogleScholarGoogle Scholar |

Schuette RD (1965) Preparing reproducible pine needle fuel beds. Research Note INT-36. (USDA Forest Service, Intermountain Forest and Range Experiment Station: Ogden, UT)

Sekimoto K, Koss AR, Gilman JB, Selimovic V, Coggon MM, Zarzana KJ, Yuan B, Lerner BM, Brown SS, Warneke C, Yokelson RJ, Roberts JM, de Gouw J (2018) High- and low-temperature pyrolysis profiles describe volatile organic compound emissions from western US wildfire fuels. Atmospheric Chemistry and Physics 18, 9263–9281.
High- and low-temperature pyrolysis profiles describe volatile organic compound emissions from western US wildfire fuels.Crossref | GoogleScholarGoogle Scholar |

Senneca O, Ciaravolo S, Nunziata A (2007) Composition of the gaseous products of pyrolysis of tobacco under inert and oxidative conditions. Journal of Analytical and Applied Pyrolysis 79, 234–243.
Composition of the gaseous products of pyrolysis of tobacco under inert and oxidative conditions.Crossref | GoogleScholarGoogle Scholar |

Shafizadeh F (1982) Introduction to pyrolysis of biomass. Journal of Analytical and Applied Pyrolysis 3, 283–305.
Introduction to pyrolysis of biomass.Crossref | GoogleScholarGoogle Scholar |

Shafizadeh F (1984) The chemistry of pyrolysis and combustion. In ‘The Chemistry of Solid Wood’. (Ed. R Rowell) Advances in chemistry. pp. 489–529. (American Chemical Society: Washington, D.C.)
| Crossref |

Shafizadeh F, Fu YL (1973) Pyrolysis of cellulose. Carbohydrate Research 29, 113–122.
Pyrolysis of cellulose.Crossref | GoogleScholarGoogle Scholar |

Sharpe SW, Johnson TJ, Sams RL, Chu PM, Rhoderick GC, Johnson PA (2004) Gas-phase databases for quantitative infrared spectroscopy. Appl Spectrosc 58, 1452–1461.
Gas-phase databases for quantitative infrared spectroscopy.Crossref | GoogleScholarGoogle Scholar |

Srivastava MS (2007) ‘Testing the equality of two covariance matrices and independence of two sub-vectors with fewer observations than the dimension.’ (University of North Carolina at Greensboro: Greensboro, NC)

Srivastava MS, Yanagihara H (2010) Testing the equality of several covariance matrices with fewer observations than the dimension. Journal of Multivariate Analysis 101, 1319–1329.
Testing the equality of several covariance matrices with fewer observations than the dimension.Crossref | GoogleScholarGoogle Scholar |

Srivastava MS, Yanagihara H, Kubokawa T (2014) Tests for covariance matrices in high dimension with less sample size. Journal of Multivariate Analysis 130, 289–309.
Tests for covariance matrices in high dimension with less sample size.Crossref | GoogleScholarGoogle Scholar |

Strand T, Gullett B, Urbanski S, O’Neill S, Potter B, Aurell J, Holder A, Larkin N, Moore M, Rorig M (2016) Grassland and forest understorey biomass emissions from prescribed fires in the south-eastern United States – RxCADRE 2012. International Journal of Wildland Fire 25, 102–113.
Grassland and forest understorey biomass emissions from prescribed fires in the south-eastern United States – RxCADRE 2012.Crossref | GoogleScholarGoogle Scholar |

Susott RA (1982a) Characterization of the thermal properties of forest fuels by combustible gas analysis. Forest Science 28, 404–420.
Characterization of the thermal properties of forest fuels by combustible gas analysis.Crossref | GoogleScholarGoogle Scholar |

Susott RA (1982b) Differential scanning calorimetry of forest fuels. Forest Science 28, 839–851.
Differential scanning calorimetry of forest fuels.Crossref | GoogleScholarGoogle Scholar |

Susott RA, DeGroot WF, Shafizadeh F (1975) Heat content of natural fuels. Journal of Fire and Flammability 6, 311–325.

Susott RA, Shafizadeh F, Aanerud TW (1979) A quantitative thermal analysis technique for combustible gas detection. Journal of Fire and Flammability 10, 94–103.

Tasoglou A, Subramanian R, Pandis SN (2018) An inter-comparison of black-carbon-related instruments in a laboratory study of biomass burning aerosol. Aerosol Science and Technology 52, 1320–1331.
An inter-comparison of black-carbon-related instruments in a laboratory study of biomass burning aerosol.Crossref | GoogleScholarGoogle Scholar |

Tihay V, Gillard P (2010) Pyrolysis gases released during the thermal decomposition of three Mediterranean species. Journal of Analytical and Applied Pyrolysis 88, 168–174.
Pyrolysis gases released during the thermal decomposition of three Mediterranean species.Crossref | GoogleScholarGoogle Scholar |

Urbanski SP, Hao WM, Baker S (2008) Chemical composition of wildland fire emissions. In ‘Wildland Fires and Air Pollution’. (Eds A Bytnerowicz, MJ Arbaugh, AR Riebau, C Andersen) Developments in Environmental Science. pp. 79–107. (Elsevier: Amsterdam, The Netherlands)
| Crossref |

van den Boogaart KG, Tolosana-Delgado R (2013) ‘Analyzing compositional data with R.’ (Springer: Heidelberg)

Wang H, Lou S, Huang C, Qiao L, Tang X, Chen C, Zeng L, Wang Q, Zhou M, Lu S, Yu X (2014) Source profiles of volatile organic compounds from biomass burning in Yangtze River Delta, China. Aerosol and Air Quality Research 14, 818–828.
Source profiles of volatile organic compounds from biomass burning in Yangtze River Delta, China.Crossref | GoogleScholarGoogle Scholar |

Ward DE (2001) Combustion chemistry and smoke. In ‘Forest Fires: Behavior and Ecological Effects’. (Eds EA Johnson, K Miyanishi) pp. 55–77. (Academic Press: San Diego, CA)
| Crossref |

Ward DE, Hao WM (1991) ‘Projections of emissions from burning of biomass for use in studies of global climate and atmospheric chemistry.’ p. 19. (Air and Waste Management Association: Vancouver, British Columbia, Canada) Available at http://www.treesearch.fs.fed.us/pubs/43258

Ward DE, Radke LF (1993) Emissions measurement from vegetation fires: a comparative evaluation of methods and results. In ‘Fire in the environment: the ecological, atmospheric, and climatic importance of vegetation fires: report of the Dahlem Workshop, held in Berlin, 15–20 March 1992’. (Eds PJ Crutzen, JG Goldammer) pp. 53–76. (John Wiley & Sons Ltd) Available at http://www.fs.fed.us/rm/pubs_other/rmrs_1993_ward_d001.pdf

Warneke C, Roberts JM, Veres P, Gilman J, Kuster WC, Burling I, Yokelson R, de Gouw JA (2011) VOC identification and inter-comparison from laboratory biomass burning using PTR-MS and PIT-MS. International Journal of Mass Spectrometry 303, 6–14.
VOC identification and inter-comparison from laboratory biomass burning using PTR-MS and PIT-MS.Crossref | GoogleScholarGoogle Scholar |

Weise DR, Johnson TJ, Reardon J (2015) Particulate and trace gas emissions from prescribed burns in southeastern U.S. fuel types: Summary of a 5-year project. Fire Safety Journal 74, 71–81.
Particulate and trace gas emissions from prescribed burns in southeastern U.S. fuel types: Summary of a 5-year project.Crossref | GoogleScholarGoogle Scholar |

Weise DR, Jung H, Palarea-Albaladejo J, Cocker DR (2020a) Compositional data analysis of smoke emissions from debris piles with low-density polyethylene. Journal of the Air & Waste Management Association 70, 834–845.
Compositional data analysis of smoke emissions from debris piles with low-density polyethylene.Crossref | GoogleScholarGoogle Scholar |

Weise DR, Palarea‐Albaladejo J, Johnson TJ, Jung H (2020b) Analyzing wildland fire smoke emissions data using compositional data techniques. Journal of Geophysical Research: Atmospheres 125, e2019JD032128
Analyzing wildland fire smoke emissions data using compositional data techniques.Crossref | GoogleScholarGoogle Scholar |

Weise DR, Fletcher TH, Johnson TJ, Hao W, Dietenberger MA, Princevac M, Butler BW, McAllister S, O’Brien JJ, Loudermilk EL, Ottmar RD, Hudak AT, Kato A, Shotorban B, Mahalingam S, Mell WE, Boardman CR, Myers TL, Baker SP, Bright BC, Restaino JC (2022a) Fundamental measurements and modeling of prescribed fire behavior in the naturally heterogeneous fuel beds of southern pine forests. Final Report RC-2640. (USDA Forest Service, Pacific Southwest Research Station: Albany, CA) Available at https://apps.dtic.mil/sti/pdfs/AD1180629.pdf

Weise DR, Fletcher TH, Safdari M-S, Amini E, Palarea-Albaladejo J (2022b) Application of compositional data analysis to determine the effects of heating mode, moisture status and plant species on pyrolysates. International Journal of Wildland Fire 31, 24–45.
Application of compositional data analysis to determine the effects of heating mode, moisture status and plant species on pyrolysates.Crossref | GoogleScholarGoogle Scholar |

Weise DR, Hao WM, Baker S, Princevac M, Aminfar A-H, Palarea-Albaladejo J, Ottmar RD, Hudak AT, Restaino J, O’Brien JJ (2022c) Comparison of fire-produced gases from wind tunnel and small field experimental burns. International Journal of Wildland Fire 31, 409–434.
Comparison of fire-produced gases from wind tunnel and small field experimental burns.Crossref | GoogleScholarGoogle Scholar |

Westbrook CK, Dryer FL (1981) Simplified reaction mechanisms for the oxidation of hydrocarbon fuels in flames. Combustion Science and Technology 27, 31–43.
Simplified reaction mechanisms for the oxidation of hydrocarbon fuels in flames.Crossref | GoogleScholarGoogle Scholar |

White JU (1942) Long optical paths of large aperture. Journal of the Optical Society of America 32, 285–288.
Long optical paths of large aperture.Crossref | GoogleScholarGoogle Scholar |

Yokelson RJ, Griffith DWT, Ward DE (1996) Open-path Fourier transform infrared studies of large-scale laboratory biomass fires. Journal of Geophysical Research: Atmospheres 101, 21067
Open-path Fourier transform infrared studies of large-scale laboratory biomass fires.Crossref | GoogleScholarGoogle Scholar |

Yokelson RJ, Karl T, Artaxo P, Blake DR, Christian TJ, Griffith DWT, Guenther A, Hao WM (2007) The Tropical Forest and Fire Emissions Experiment: overview and airborne fire emission factor measurements. Atmospheric Chemistry and Physics 7, 5175–5196.
The Tropical Forest and Fire Emissions Experiment: overview and airborne fire emission factor measurements.Crossref | GoogleScholarGoogle Scholar |

Yokelson RJ, Burling IR, Gilman JB, Warneke C, Stockwell CE, de Gouw J, Akagi SK, Urbanski SP, Veres P, Roberts JM, Kuster WC, Reardon J, Griffith DWT, Johnson TJ, Hosseini S, Miller JW, Cocker III DR, Jung H, Weise DR (2013) Coupling field and laboratory measurements to estimate the emission factors of identified and unidentified trace gases for prescribed fires. Atmospheric Chemistry and Physics 13, 89–116.
Coupling field and laboratory measurements to estimate the emission factors of identified and unidentified trace gases for prescribed fires.Crossref | GoogleScholarGoogle Scholar |

Zhou X, Mahalingam S (2001) Evaluation of reduced mechanism for modeling combustion of pyrolysis gas in wildland fire. Combustion Science and Technology 171, 39–70.
Evaluation of reduced mechanism for modeling combustion of pyrolysis gas in wildland fire.Crossref | GoogleScholarGoogle Scholar |